# How to connect MoSPI to Grok Bot

```json
{
  "title": "How to connect MoSPI to Grok Bot",
  "toolkit": "MoSPI MCP",
  "toolkit_slug": "mospi_mcp",
  "framework": "Grok Bot",
  "framework_slug": "grok-bot",
  "url": "https://composio.dev/toolkits/mospi_mcp/framework/grok-bot",
  "markdown_url": "https://composio.dev/toolkits/mospi_mcp/framework/grok-bot.md",
  "updated_at": "2026-10-04T17:43:40.153Z"
}
```

## Introduction

Grok is xAI's assistant, and its bot builder lets you create a personal agent that holds context, runs skills, and connects to the apps you already use through plugins.
This guide explains how to connect MoSPI to a Grok bot using Composio Connect, which handles OAuth, token refresh, and reliability so you do not have to. You add Composio as a plugin, authenticate once, then ask your bot to work with MoSPI in plain language.

## Also integrate MoSPI MCP with

- [ChatGPT](https://composio.dev/toolkits/mospi_mcp/framework/chatgpt)
- [Claude Cowork](https://composio.dev/toolkits/mospi_mcp/framework/claude-cowork)

## TL;DR

Composio exposes 1,500+ apps to your Grok bot through a single connection, so you get:
- Connect to 1,500+ apps with on-demand tool loading, so you do not fill your context window with unnecessary tool definitions.
- Use programmatic tool calling through a remote workbench, letting the model write its own code to handle complex tool chaining. This reduces back-and-forth for frequent tool calls.
- Handle large tool responses outside the model context to keep conversations lean.

## Connect MoSPI MCP to Grok Bot

### Connecting MoSPI to Grok Bot
Once Grok Bot is set up, you connect MoSPI entirely from its interface, and the whole flow takes under a minute.
### Set up Grok Bot
Get access. Grok Bot is included with Cursor Ultra, Cursor Premium Teams, and SuperGrok Heavy. Get the desktop app for macOS or Windows from [x.ai/bot](https://x.ai/bot) and sign in. An iPhone companion app is also available, and your bots sync across devices.
Create a bot. Pick a suggested role or define your own, then give it a short name, one primary job, and a short description of how it should work. Focused bots work best, because a clear role gives the bot more useful context over time.
### Connect MoSPI
### 1. Add the Composio plugin
Click the button. The Composio listing on x.ai opens and launches Grok Bot for you. If the app does not open on its own, click Add to Grok Bot.
[Add to Grok Bot](https://x.ai/bot/plugin/32661537)
Grok Bot opens the Composio plugin, showing its connector and skills. Click Add.
### 2. Authenticate
Go to the Installed section and click the Composio entry. You'll see its connector and skills listed.
Click Authenticate. You'll be taken to the Composio consent screen. Review the access it requests and click Authorize. Composio handles the OAuth handshake for you, so you never touch API keys or tokens.
### 3. Connect your MoSPI account
Back in the chat, ask your bot to connect to MoSPI or give it any MoSPI task.
For example, ask it to:
- "Summarize latest Indian CPI inflation trends"
- "Compare recent IIP growth by sector"
- "Find unemployment statistics from MoSPI reports"
It will prompt you to authenticate and authorize access.
That's it. Composio's tools are now available in your Grok bot, and your MoSPI account is ready to use.

## What is Grok Bot?

Grok is xAI's assistant, available as a chat interface and a bot builder for creating personal agents that run skills and connect to external apps.
With Composio Connect, your Grok bot can securely access apps like MoSPI through MCP without you sharing account credentials directly with the agent.

## What is the MoSPI MCP server, and what's possible with it?

The MoSPI MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to MoSPI. It provides structured and secure access to India's official statistical datasets, so your agent can discover datasets, explore indicators, identify valid filters, and fetch statistical data on your behalf.
- Dataset discovery: Have your agent list available MoSPI datasets and review their descriptions and coverage.
- Indicator exploration: Let the agent find all available indicators within a selected statistical dataset.
- Filter identification: Direct your agent to check valid states, years, quarters, and other filters for a dataset and indicator.
- Statistical data retrieval: Instruct your agent to fetch official statistics from a chosen dataset using the relevant indicators and filters.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `MOSPI_MCP_GET_DATA` | Get data | Fetches statistical data from a MoSPI dataset. This is the final step of the workflow. It requires filter values from get_metadata — filter codes are arbitrary (e.g., indicator_code=3 means "Unemployment Rate" in PLFS but something different in other datasets). All filter parameters including limit and page go inside the filters dict, not as top-level arguments. Step 4 of: list_datasets → get_indicators → get_metadata → get_data |
| `MOSPI_MCP_GET_INDICATORS` | Get indicators | Returns the full list of available indicators for a given dataset. Datasets often have broader coverage than expected — for example, ASI covers 57 indicators (capital structure, wages, employment, GVA, fuel consumption), and GENDER covers 147 indicators across health, education, labor, and crime. For PLFS and ASUSE, indicators are grouped by frequency_code: - PLFS frequency_code=1 (Annual): all 8 indicators including wages - PLFS frequency_code=2 (Quarterly): indicators 1-3 only - PLFS frequency_code=3 (Monthly): indicators 1-3 only frequency_code selects the indicator set, not time granularity. Step 2 of: list_datasets → get_indicators → get_metadata → get_data |
| `MOSPI_MCP_GET_METADATA` | Get metadata | Returns the valid filter values (states, years, quarters, etc.) for a given dataset and indicator. Filter codes are arbitrary and dataset-specific — for example, PLFS state_code 99 means "All India", and NAS frequency_code 1 means "Annual". These values cannot be inferred or guessed from parameter names alone. The returned filter_values and api_params should be used as-is when calling get_data. Step 3 of: list_datasets → get_indicators → get_metadata → get_data |
| `MOSPI_MCP_LIST_DATASETS` | List datasets | Returns an overview of all MoSPI statistical datasets with descriptions and coverage. This is the starting point ΓÇö call this first to identify the right dataset. The API covers 500+ indicators across employment, prices, industry, national accounts, health, education, disability, housing, environment, trade, and more. Each dataset has its own indicator codes, filter parameters, and valid values ΓÇö these are not standardized and cannot be inferred or guessed from parameter names alone. Four-step workflow (each step depends on the previous): 1. list_datasets() ΓÇö identify the dataset 2. get_indicators(dataset) ΓÇö list available indicators 3. get_metadata(dataset, indicator_code) ΓÇö retrieve valid filter values 4. get_data(dataset, filters) ΓÇö fetch the data Returns: dict with 'datasets' (name, description, use_for for each dataset) and 'workflow' (the four-step sequence). |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

Once connected, your Grok bot can access the MoSPI MCP server through Composio to run the actions you authorize, using plain language in the chat.

## Complete Code

None listed.

## Conclusion

### Way Forward
Now that MoSPI is connected, extend your setup by connecting the other apps you already use every day, so your Grok bot can run true cross-app workflows end to end.
- Connect Calendar to turn threads into scheduled meetings automatically.
- Connect Slack or Teams to post summaries, approvals, and alerts where your team works.
- Connect Notion, Linear, Jira, or Asana to convert requests into tickets, tasks, and docs.
- Connect Drive, Dropbox, or OneDrive to fetch, file, and share attachments without manual steps.
Start with one workflow you do repeatedly, then keep adding apps as you find new handoffs. With everything behind a single connection, your bot can coordinate multiple tools safely and reliably in one conversation.

## How to build MoSPI MCP Agent with another framework

- [ChatGPT](https://composio.dev/toolkits/mospi_mcp/framework/chatgpt)
- [Claude Cowork](https://composio.dev/toolkits/mospi_mcp/framework/claude-cowork)

## Related Toolkits

- [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. It's the go-to tool for calculations, reporting, and flexible data management.
- [21risk](https://composio.dev/toolkits/_21risk) - 21RISK is a web app built for easy checklist, audit, and compliance management. It streamlines risk processes so teams can focus on what matters.
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- [Adafruit IO](https://composio.dev/toolkits/adafruit_io) - Adafruit IO is Adafruit's cloud platform for connected device and IoT project data. It helps you store, visualize, and act on sensor feeds without running your own backend.
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- [Ambee](https://composio.dev/toolkits/ambee) - Ambee is an environmental data platform providing real-time, hyperlocal APIs for air quality, weather, and pollen. Get precise environmental insights to power smarter decisions in your apps and workflows.
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- [Anonyflow](https://composio.dev/toolkits/anonyflow) - Anonyflow is a service for encryption-based data anonymization and secure data sharing. It helps organizations meet GDPR, CCPA, and HIPAA data privacy compliance requirements.
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- [Apify](https://composio.dev/toolkits/apify) - Apify is a cloud platform for building, deploying, and managing web scraping and automation tools called Actors. It lets you automate data extraction and workflow tasks at scale—no infrastructure headaches.
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- [Bigpicture io](https://composio.dev/toolkits/bigpicture_io) - BigPicture.io offers APIs for accessing detailed company and profile data. Instantly enrich your applications with up-to-date insights on 20M+ businesses.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and MoSPI MCP?

With a standalone MoSPI MCP server, the agents and LLMs can only access a fixed set of MoSPI tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from MoSPI and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with Grok Bot?

Yes, you can. Grok Bot fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right MoSPI tools.

### Can I manage the permissions and scopes for MoSPI while using Tool Router?

Yes, absolutely. You can configure which MoSPI scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

### How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your MoSPI data and credentials are handled as safely as possible.

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